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Accounting Information System

Autor:   •  March 13, 2018  •  Course Note  •  2,727 Words (11 Pages)  •  896 Views

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Accounting, Business Reporting and Business Intelligence (20 marks) week7 8  

Week 7

Objectives: (Read Chapter 7 and Chapter 8 of the text book, We now focus on how accounting data can be analysed, and viewed using sustainability intelligence.)

Describe the relationship between transactional databases, data warehouses and business intelligence (BI)

Explain how data cubes form the basis of data analysis

Give examples of business intelligence tools

Identify advantages and disadvantages of business intelligence

Describe the relationship between BI, sustainability and integrated reporting

What is an integrated decision model?

Decision models facilitate data collection for the decision making process. The Integrated Decision Model (IDM) considers both quantitative and qualitative factors in decision making.

What are the four components of an intelligent enterprise system? 

The four components of an intelligent enterprise system are:

 Data storage

 Data extraction and transfer

 Data analysis

 Data visualization

What are two approaches to business intelligence?

1. Shadow data. Shadow data shadows the formal accounting system and often resides in spreadsheets on computer desktops and laptops.

2. Business intelligence technologies. BI technologies include business analytics, data mining, and predictive modeling.

What is global spreadsheet identification?

To improve security over shadow data in spreadsheets, global spreadsheet identification is recommended. Each spreadsheet is assigned a spreadsheet identifier, or SSID, similar to a primary key for database record identification.

What database structure does a data warehouse use?

Data warehouses use a dimensional database structure, such as the star structure. This dimensional structure allows faster access and retrieval of massive amounts of data for BI technologies.

How do shadow data and BI technologies compare?

Business intelligence can be divided into two general categories: shadow data and BI technologies. The four components of an intelligent system are data storage, extraction and transfer (type of query), analysis tools, and visualization tools (output format). Shadow data and BI technologies vary across these four components.

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